Reservoir Computing and Photoelectrochemical Sensors: A Marriage of Convenience

Abstract

Sensing technology is an important aspect of information processing. Current development in artificial intelligence systems (especially those aimed at medical and environmental applications) requires a lot of data on the chemical composition of biological fluids or environmental samples. These complex matrices require advanced sensing devices, and photoelectrochemical ones seem to have potential to overcome at least some of the obstacles. Furthermore, the development of artificial intelligence (AI) technology for autonomous robotics requires technology mimicking human senses, also those operating at the molecular level, such as gustation and olfaction. Again, photoelectrochemical sensing can provide some suitable solutions. In this review, we introduce the idea of integration of photoelectrochemical sensors with some unconventional computing paradigm - reservoir computing. This approach should not only boost the performance of the sensors itself, but also open new pathways through science. Integration of sensing devices with computing systems will also contribute to a better understanding (or at least mimicking) of the human senses and neuromorphic sensory information processing. Although reservoir systems can be considered magic "black boxes" and their operation is at the same time simple and hard to comprehend, this combination is expected to open a new era of effective information harvesting and processing systems.

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